Customized options for consumption of content

ABSTRACT

Systems and methods for consuming content. A computing device may receive data. The computing device may determine an inference. The computing device may manage content. The computing device may manage content based on the inference.

CROSS REFERENCE TO RELATED PATENT APPLICATION

This application is a continuation of U.S. patent application Ser. No.16/172,392, filed Oct. 26, 2018, which is a continuation of U.S. patentapplication Ser. No. 13/559,341 (now U.S. Pat. No. 10,158,898), filedJul. 26, 2012, each of which is herein incorporated by reference in itsentirety.

BACKGROUND

Generation of suggestions for consumption of content typically is basedon heterogeneous segments of consumers. Certain service providers haveutilized online methods for generating such suggestions based on, forexample, collection of data related to a user's recent consumption ofcontent assets (e.g., two recently viewed movies) and rating thereofaccording to a fixed scale (such as a scale ranging from one to five).Aggregated or merely cumulative data are then compared against either adatabase or other users within a specific consumer segment to generate alist of suggestions. In addition or in the alternative, polling ofconsumers (e.g., a voting solution, such as voting for two contentassets of value) generally rely on comparisons against other user'sselection of content assets in order to create viewing suggestions. Yet,such customization of content largely fails to incorporate personalizedactive consumption trends.

SUMMARY

It is to be understood that this summary is not an extensive overview ofthe disclosure. This summary is exemplary and not restrictive, and it isintended to neither identify key or critical elements of the disclosurenor delineate the scope thereof. The sole purpose of this summary is toexplain and exemplify certain concepts of the disclosure as anintroduction to the following complete and extensive detaileddescription.

The disclosure relates, in one aspect, to generating personalizedoptions for consumption of content, such as media assets (or contentassets) comprising linear-programming assets, non-linear-programmingassets, or recorded media assets. Such content can have remote presence(e.g., stored in a network) or local presence (e.g., stored in a devicecoupled to a network). The personalized options can permitadministration of the media assets based at least on consumptionbehavior of an end-user. For instance, the personalized options canpermit automated generation of storage configuration(s) and/or playbackconfiguration(s).

Some embodiments of the disclosure provide various advantages whencompared to conventional technologies for routing traffic in an activereplication topology. For example, based on machine learning, thedisclosure provides one or more personalized options (e.g., viewingoptions) that can adapt to, at least, frequency of consumption of amedia asset. For another example, the disclosure provides options forautomated administration of consumption of recorded assets being storedlocally and/or remotely in a network repository.

Additional aspects or advantages of the subject disclosure are set forthin part in the description which follows, and in part will be obviousfrom the description, or may be learned by practice of the subjectdisclosure. The advantages of the subject disclosure can be realized andattained by means of the elements and combinations particularly pointedout in the appended claims. It is to be understood that both theforegoing general description and the following detailed description areexemplary and explanatory only and are not restrictive of thedisclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The annexed drawings are an integral part of the subject disclosure andillustrate exemplary embodiments thereof. Together with the descriptionset forth herein and the claims appended hereto, the annexed drawingsserve to explain various principles, features, or aspects of the subjectdisclosure.

FIGS. 1A-1B illustrate exemplary network environments in accordance withone or more aspects of the disclosure.

FIG. 2 illustrates an exemplary network in accordance with one or moreaspects of the subject disclosure.

FIGS. 3-4 illustrate exemplary embodiments of computing devices inaccordance with one or more aspects described herein.

FIGS. 5-7 illustrate exemplary methods in accordance with one or moreaspects of the disclosure.

DETAILED DESCRIPTION

The various aspects described herein can be understood more readily byreference to the following detailed description of exemplary embodimentsof the subject disclosure and to the annexed drawings and their previousand following description.

Before the present systems, articles, apparatuses, and methods aredisclosed and described, it is to be understood that the subjectdisclosure is not limited to specific systems, articles, apparatuses,and methods for generating personalized options for consumption of mediaassets comprising linear-programming assets or recorded media assetshaving remote presence (e.g., stored in a network) or local presence(e.g., stored in a device coupled to a network). The personalizedoptions can permit administration of the media assets (e.g., automatedgeneration of storage configuration(s) and/or playback configuration(s))based at least on consumption behavior of an end-user. It is also to beunderstood that the terminology employed herein is for the purpose ofdescribing particular, non-exclusive embodiments only and is notintended to be limiting.

As used in the specification and the appended claims, the singular forms“a,” “an” and “the” include plural referents unless the context clearlydictates otherwise. Ranges may be expressed herein as from “about” oneparticular value, and/or to “about” another particular value. When sucha range is expressed, another embodiment includes from the oneparticular value and/or to the other particular value. Similarly, whenvalues are expressed as approximations, by use of the antecedent“about,” it will be understood that the particular value forms anotherembodiment. It will be further understood that the endpoints of each ofthe ranges are significant both in relation to the other endpoint, andindependently of the other endpoint.

As utilized in this specification and the annexed drawings, the terms“system,” “layer,” “component,” “unit,” “interface,” “platform,” “node,”“function” and the like are intended to include a computer-relatedentity or an entity related to an operational apparatus with one or morespecific functionalities, wherein the computer-related entity or theentity related to the operational apparatus can be either hardware, acombination of hardware and software, software, or software inexecution. Such entities also are referred to as “functional elements.”As an example, a unit can be, but is not limited to being, a processrunning on a processor, a processor, an object (metadata object, dataobject, signaling object), an executable computer program, a thread ofexecution, a program, a memory (e.g., a hard-disc drive), and/or acomputer. As another example, a unit can be an apparatus with specificfunctionality provided by mechanical parts operated by electric orelectronic circuitry which is operated by a software application or afirmware application executed by a processor, wherein the processor canbe internal or external to the apparatus and can execute at least aportion of the software application or the firmware application. As yetanother example, a unit can be an apparatus that provides specificfunctionality through electronic functional elements without mechanicalparts, the electronic functional elements can include a processortherein to execute software or firmware that provides, at least in part,the functionality of the electronic functional elements. The foregoingexamples and related illustrations are but a few examples and are notintended to be limiting. In addition, while such illustrations arepresented for a unit, the foregoing examples also apply to a system, alayer, a node, an interface, a function, a component, a platform, andthe like. It is noted that in certain embodiments, or in connection withcertain aspects or features such embodiments, the terms “system,”“layer,” “unit,” “component,” “interface,” “platform” “node,” “function”can be utilized interchangeably.

Throughout the description and claims of this specification, the words“comprise,” “include,” and “having” and their variations, such as“comprising” and “comprises,” “include” and “including,” “having” and“has,” mean “including but not limited to,” and are not intended toexclude, for example, other units, nodes, components, functions,interfaces, actions, steps, or the like. “Exemplary” means “an exampleof” and is not intended to convey an indication of a preferred or idealembodiment. “Such as” is not used in a restrictive sense, but forexplanatory purposes.

Disclosed are components that can be utilized to perform the disclosedmethods, devices, and/or systems. These and other components aredisclosed herein, and it is understood that when combinations, subsets,interactions, groups, etc. of these components are disclosed that whilespecific reference of each various individual and collectivecombinations and permutation(s) of these may not be explicitlydisclosed, each is specifically contemplated and described herein, forall methods, devices, and/or systems. This applies to all aspects of thesubject disclosure including steps, or actions, in the disclosedmethod(s). Thus, if there are a variety of additional steps, or actions,that can be performed, then it is understood that each of suchadditional steps, or actions, can be performed with any specificembodiment or combination of embodiments of the disclosed methods.

As it will be readily appreciated, in one aspect, the methods, devices,and/or systems of the disclosure can take the form of an entirelyhardware embodiment, an entirely software embodiment, or an embodimentcombining software and hardware aspects. In an additional or alternativeaspect, the methods, devices, and/or systems can take the form of acomputer program product on a computer-readable storage medium havingcomputer-readable program instructions (e.g., computer software)embodied in the storage medium. More particularly, the disclosedmethods, devices, and/or systems can take the form of web-implementedcomputer software. Any suitable computer-readable storage medium can beutilized including hard disks, CD-ROMs, optical storage devices, ormagnetic storage devices.

Embodiments of the methods and systems are described below withreference to block diagrams and flowchart and/or call-flow illustrationsof methods, systems, apparatuses and computer program products. It willbe understood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, respectively, can be implemented by computerprogram instructions. Such computer program instructions may be loadedonto a general purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions which execute on the computer or other programmabledata processing apparatus create a means for implementing the functionsspecified in the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including computer-readableinstructions for implementing the function specified in the flowchartblock or blocks. The computer program instructions also can be loadedonto a computer or other programmable data processing apparatus to causea series of operational steps, or acts, to be performed on the computeror other programmable apparatus to produce a computer-implementedprocess such that the instructions that execute on the computer or otherprogrammable apparatus provide steps for implementing the functionsspecified in the flowchart block or blocks.

Accordingly, blocks of the block diagrams and flowchart illustrationssupport combinations of means for performing the specified functions,combinations of steps for performing the specified functions and programinstruction means for performing the specified functions. It will alsobe understood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, can be implemented by special purposehardware-based computer systems that can perform the specified functionsor steps, or combinations of special purpose hardware and computerinstructions.

Reference will now be made in detail to the various embodiments andrelated aspects of the subject disclosure, examples of which areillustrated in the accompanying drawings and their previous andfollowing description. Wherever possible, the same reference numbers areused throughout the drawings to refer to the same or like parts.

The disclosure identifies and addresses, in one aspect, the complexityand difficulty of customizing media programming for the generalmedia-consuming public. As described in greater detail below, in oneaspect, the disclosure relates to generating personalized options forconsumption of media assets comprising linear-programming assets orrecorded media assets having remote presence (e.g., stored in a network)or local presence (e.g., stored in a device coupled to a network). Inone aspect, the personalized options can be supplied (e.g., transmitted)asynchronously, based at least on availability of a media asset, and canbe indicative of information associated with a media asset of likelyinterest to an end user. In another aspect, the personalized options canpermit administration of the media assets (e.g., automated generation ofstorage configuration(s) and/or playback configuration(s)) based atleast on consumption behavior of an end-user. It should be appreciatedthat the personalized options described herein can be referred to as“atomic options” in that the options are customized for a singleend-user according to historical data directly associated with mediaconsumption behavior for the single user. Certain functional elements ofthe subject disclosure can be implemented (e.g., performed) by software,hardware, or a combination of software and hardware. Functional elementsof the various embodiments described in the present specification andillustrated in the annexed drawings can be employed in operationalenvironments (access network, telecommunication network, signalingnetwork, etc.) that can include, for example, digital equipment, analogequipment, or both, wired or wireless equipment, etc.

FIGS. 1A-1B are block diagrams of exemplary systems 100 and 180,respectively, that permit customization of consumption of media assetsin accordance with one or more aspects of the disclosure. As describedherein, certain features of such administration can be automated. Theexemplary system 100 comprises a rendering device 110 functionallycoupled (e.g., communicatively coupled) to an exchange device 120 (e.g.,a set-top box, a personal computer, a mobile computer, a wearabledevice, or the like) via a data and signaling pipe 115. In one aspect,to enable such coupling, the data and signaling pipe 115 can befunctionally coupled to at least one input/output (I/O) interface of theone or more interfaces 112 at the rendering device 110 and to at leastone I/O interface of the one or more I/O interfaces 124. The data andsignaling pipe 115 can comprise an upstream link, or uplink (UL), and adownstream link, or downlink (DL). The UL flow of information isrepresented with an arrow oriented outwards from the rendering device110, whereas the DL flow of information is represented with an arroworiented towards the exchange device 120. The data and signaling pipe115 can comprise one or more of: a reference link (Cx, Cr, Dh, Dx, Gm,Ma, Mg, or the like) and related components; conventional busarchitectures such as address buses, system buses; wired links, such ashigh definition multimedia interface (HDMI) cables, fiber optic lines,coaxial lines, hybrid fiber-coaxial links, Ethernet lines, T-carrierlines, twisted-pair line, or the like, and various connectors (e.g., anEthernet connector, an F connector, an RS-232 connector, or the like);wireless links, including one or more of terrestrial wireless links,satellite-based wireless links, or a combination thereof; and so forth.

As illustrated, the rendering device 110 can comprise a display unit 114that can receive content (e.g., metadata or data, or both) and/orsignaling from an I/O interface of the one or more I/O interfaces 112.Such I/O interface can be or can comprise a HDMI, which can receivecontrol input 104, such as data and/or signaling indicative of aninstruction to control the rendering device 110. In one aspect, theinstruction can be received from a remote control or other control unit(not depicted) and can be directed to one or more of adjusting volume ofaudio of a rendered media asset, switching a channel tuned by theexchange device 120, or the like. At least a portion of the contentand/or the signaling can be received from the exchange device 120through the downlink (DL) of the data and signaling pipe 115. Thedisplay unit 114 can render at least a portion of the received content.In one embodiment, for example, the display unit 114 can comprise arendering medium (a liquid crystal layer, a plasma layer, etc.) andbacklight system (e.g., a light-emitting-diode lighting system) andrelated circuitry.

As illustrated, the exchange device 120 can exchange content andsignaling (e.g., control messages) with a network 160 via data andsignaling pipe 155, the pipe 155 enabling functional coupling thatpermits such exchange. In one aspect, the exchange device 120 cantransmit at least a portion of one or more inference(s) 137 to therepository 164. The network 110 can be, for example, a service network,and such coupling permits, at least in part, the network 110 to providea service. The content can include media assets (e.g., audio, images,video, or combinations thereof)) and related metadata, the media assetscomprising linear-programming assets and recorded media assets. Exchangedevice 120 can transmit at least a portion of the content exchanged withthe network 160 to the rendering device 110 for consumption at therendering device 110. Similarly to data and signaling pipe 115, the dataand signaling pipes 155 can include one or more of wireless links, wireline links, or a combination thereof. In certain implementations, forexample, the data and signaling pipe 155 can comprise one or more of: areference link (Cx, Cr, Dh, Dx, Gm, Ma, Mg, or the like) and relatedcomponents; conventional bus architectures such as address buses, systembuses; wired links, such as fiber optic lines, coaxial lines, hybridfiber-coaxial links, Ethernet lines, T-carrier lines, twisted-pair line,or the like, and various connectors (e.g., Ethernet connectors, Fconnectors, RS-232 connectors, or the like); wireless links, includingterrestrial wireless links, satellite-based wireless links, or acombination thereof; and so forth.

It should be appreciated that the data and signaling pipe 155 isrepresented with open-head arrows, to pictorially indicate that one ormore network components (router(s), server(s), network switches(s),connector(s), hubs, etc.) can permit communication among the network 160and the exchange device 120. Communication among the exchange device 120and the network 160 or a component thereof can be accomplished, at leastin part, via data and signaling pipe 155. In one aspect, suchcommunication can be effected in accordance with one or morepacket-switched protocols, such as Ethernet protocol format; internetprotocol (IP) format, such as IPv4 and IPv6, or the like; TCP/IP; userdatagram protocol (UDP) format, HTTP, simple object access protocol(SOAP), simple network management protocol (SNMP), or the like.

In certain embodiments, the network 160 can include wireless networks,wire line networks, or a combination thereof, and can provide a serviceto one or more devices, such as user equipment, customer premisesequipment, control equipment (e.g., signaling units), operation andmaintenance (O&M) equipment (e.g., network probes), and the like. In oneaspect, the service provided by the network 160 can be a consumerservice, such as content communication (media on demand, Internetservice, digital telephony (e.g., voice over internet protocol (VoIP)),multimedia message service (MMS), short message service (SMS), etc.);content management (e.g., network digital video recording, messagingadministration); emergency services (e.g., enhanced 911); location-basedservices; or the like. In another aspect, the service provided by thenetwork 160 can be a network administration service, which can compriseone or more of accounting and billing, access control, subscriberprovisioning, customer service support (including, for example,interactive voice response (IVR)), performance monitoring (e.g.,dashboard services, automation control, etc.), or the like. Architectureof the network 110 can be specific to the provided service.

The network 160 can embody or comprise one or more of a wide areanetwork (WAN), a signaling network (e.g., SS #7), an enterprise network,a local area network, a home area network, a personal area network(which can include wearable devices), or the like. Such networks canoperate in accordance with one or more communication protocols for wireline communication or wireless communication. In certain embodiments,the network 160 can have several functional elements that can provide abackbone network, such as a high-capacity packet-switched network. Inother embodiments, the network 160 can have internal structure, withseveral functional elements that can provide at least two mainoperational blocks: a backbone network (e.g., a high-capacitypacket-switched network) and a regional access network (RAN). Theinternal structure also can include functional elements that providemore spatially localized networks, such as local area networks, homearea networks, or the like. Both the backbone network and the regionalaccess network (RAN) can be WANs, for example, with the backbone networkhaving a larger geographical scope than the RAN.

In the exemplary network embodiment 100, the exchange device 120 cancomprise a knowledge generation unit 128 that can monitor (collect,receive, collect and analyze, receive and analyze, etc.) data indicativeof current or substantially current consumption of one or more pluralityof media assets. In certain scenarios, the knowledge generation unit 128can monitor (e.g., retrieve or receive) data indicative of alinear-programming media asset being rendered. In other scenarios, theknowledge generation unit 128 can monitor (e.g., retrieve or receive)data indicative of playback of a recorded media asset, such as one mediaasset of the one or more media assets 140.

Based at least on a portion of the data that is monitored (e.g.,received), the knowledge generation unit 128 can provide an inferenceassociated with prospective consumption of a specific media asset of theplurality of media assets. In one embodiment, the knowledge generationunit 128 can generate the inference associated with the prospectiveconsumption of the specific media asset. In one aspect, the inferencecan be generated periodically or at specific times (e.g., according to apredetermined schedule). In another aspect, the inference can begenerated in response to specific events, which can be configurable. Theevents can comprise one or more of a scheduling conflict, unavailablememory resources, or the like. An end-user (or consumer) or a serviceprovider (e.g., owner or lessee of network 110 or portions thereof) canconfigure such events. One or more of the generated inferences can beretained in memory 136, in a memory element referred to as inference(s)137.

To generate an inference based on monitored data, in one aspect, theknowledge generation unit 128 can classify the data that is monitoredinto two or more categories of data. In certain implementations, the twoor more categories of data can comprise a first category of datasuitable for inferring the prospective consumption of the specific mediaasset and a second category of data non-suitable for inferring theprospective consumption of the specific media asset. The first categoryof data is indicative of end-user consumption behavior over a period oftime (e.g., a consumption trend) and can comprise the portion of thedata utilized for generation of the inference. Such category of data canbe referred to as “relevant consumer behavior data.”

Accordingly, in one aspect, one or more inputs (e.g., data and/orsignaling) can permit categorization of monitored data according toparticipation level of the end user, such categorization can be includedin the classification performed by the knowledge generation unit 128. Inone scenario in which the data and signaling pipe 115 is embodied in aHDMI cable, such cable and a remote control that can supply controlinput 104 can be examples of at least two of a plurality of inputs thatcan permit the determination of relevancy of collected data related toconsumption of a media asset. In one aspect, determining value of dataassociated with a consumed media asset can include ascertaining that themedia asset is being actively consumed (e.g., actively viewed) orpassively consumed. For an end-user that can consume a media asset(e.g., watching a television show), there can be various inputs (e.g.,control input 104)—regardless of how straightforward they might be—thatcan provide elements for determining an active participation levelassociated with the end-user. In such scenario, the end-user (who may bea customer) may have disable the rendering device 110 or, in thealternative, the end-user may not be actively consuming (e.g., viewing)the media-asset, such as in a situation in which rendering of the mediaasset is initiated, but the consumer is no longer in proximity of therendering device 110 at a later time and thus the end-user no longeractively consumes the media asset.

Inputs from a physical interface and/or link (e.g., an HDMI cable)and/or inputs from a wireless interface (e.g., the air interface) and/orlink (e.g., a radiofrequency (RF) link), such as a signal received froman actuated remote control, can provide information to the exchangedevice 120—via signaling transmitted through link(s) 115, for example—asto whether the rendering device 110 is operating actively and/or whetherthe end-user is causing at least a portion of such inputs in order tointeract with or to control a rendering of the media asset. Suchinteraction or control can comprise a change in a state of the renderingof the media asset, for example, by pausing or fast forwarding renderedcontent, by actuating (physically or remotely) volume controls (mute,volume up, volume down, etc.), or by switching a channel delivering themedia asset, in case of linear programming. In addition or in thealternative, at least the portion of the inputs can permit determining adegree of consumption of the media asset. For instance, it can beascertained that the media asset is fully consumed, mostly consumed,partially consumed, or marginally consumed.

Upon or after a participation level is determined, in one aspect,frequency of consumption of the media asset can be determined,particularly for recorded media assets. In one aspect, the managementunit 132 can perform such determination. In one scenario in which amedia asset is viewed several times and/or not intentionally orotherwise deleted after consumption, it can be gleaned (via theknowledge generation unit 128, for example) that the media asset isdesirable for consumption, and therefore repeat consumption also can bedesirable.

Knowledge generation unit 128 can retain the data in the first categoryand the data in the second category in respective memory elements(registers, memory pages, files, databases, etc.) in data storage 142.In one aspect, a first memory element, represented with a block labeleddata category I 144, can contain data in the first category, a secondmemory element, represented with block labeled to as data category II146, can contain data in the second category. In one or moreembodiments, the knowledge generation unit 128 can implement artificialintelligence (AI) techniques, such as machine learning and iterativelearning, to generate an inference. Examples of such techniques include,but are not limited to, expert systems, case based reasoning, Bayesiannetworks, behavior based AI, neural networks, fuzzy systems,evolutionary computation (e.g., genetic algorithms), swarm intelligence(e.g., ant algorithms), and hybrid intelligent systems (e.g., expertinference rules generated through a neural network or production rulesfrom statistical learning).

It should be appreciated that classification of the data that ismonitored into such categories can permit separation of data into datacontaining behavioral information of a consumer (e.g., an end-user) of amedia asset and data representing operation of the rendering device 110that is not associated with such behavioral information. The secondcategory of data can originate from rendering content that is notresponsive to behavior of an end-user that can consume the content viathe rendering device 110. For instance, in one scenario, the renderingdevice 110 can render content, such as a linear-programming asset,without an end-user consuming such content—e.g., actively watching thecontent or interacting with the rendering device 110 during delivery ofthe content—thus information indicative of the linear-programming asset(e.g., “PBS” in Channel 2) being rendered for a period of, for example,4-10 hours may not suitable for generating an inference of consumptionof such asset. To classify data into the second category of data, in oneembodiment, knowledge generation unit 128 can determine that at leastthe I/O interface of I/O interface(s) 112 that receives content atrendering device 110 interface is switched off for a specific period,and during the specific period, the knowledge generation unit 128 canassign at least a portion of the data monitored (e.g., received) duringthe specific period to the second category of data.

In one embodiment, the knowledge generation unit 128 can update anextant classification of data as a function of time based on a relevancyscore Σ (e.g., a real number) determined at least in part by one or moreof specific media asset, source of the media asset (e.g., recorded assetor linear-programming asset), cumulative of a time interval ofconsumption of the media asset, and longevity of the data. In oneimplementation, the relevancy score Σ can be defined as, for example:

$\begin{matrix}{\Sigma = {\frac{t_{v} + {f\left( a_{DVR} \right)} + {g\left( a_{VOD} \right)}}{\sqrt{\Delta\; t_{v}}}.}} & {{Eq}.\mspace{11mu}(1)}\end{matrix}$Here, t_(v) represents the time period (e.g., hours) that the mediaasset has been consumed; Δt_(v) represents a time period since the mediaasset was consumed (e.g., number of days since the media asset was lastviewed); f(·) and g(·) each represent functions (e.g., real-valuedlinear functions) that can be reconfigurable and can provide a weight toΣ in response to the media asset being a recorded media asset retainedvia a digital video recording (DVR) functionality of the exchange device120, or a video-on-demand (VOD) media asset, the value of the parametera_(DVR) being 0 if the media asset is not a recorded media asset (suchas a linear-programming asset), 1 if the media asset is recorded via DVRand not viewed, and 2 if the media asset is recorded via DVR and viewed;and the value of the parameter a_(VOD) being 0 if the media asset is nota VOD non-linear asset or 1 is the media asset is a VOD non-linearasset.

In one aspect, such time-dependent update can be referred to as dataaging and can permit maintaining a categorization of data that moreclosely conveys substantially current consumer behavior over longer termhistorical data. In one aspect, the denominator in Eq. (1) is an agescaling function (also referred to as aging function). Whilesubstantially any aging function can be utilized, the square rootfunction is typically utilized as aging function because the firstderivative of the square root function has values that are large forsmall arguments (e.g., smaller than unity and greater than zero) withthe second derivative having small values for arguments greater thanabout unity. Such behavior provides an aging function that has a steepinitial increase that “levels out” for moderate values of the argumentof such function. Thus, “age penalty” of relevancy is prevented fromdominating the behavior of the relevancy score Σ while incorporatingaging scaling that increases over time, which reduces the value of Σ forlarger times.

It should be appreciated that certain aging functions, such as linearfunctions or polynomial functions, can yield small aging effects as timeelapses from a present time. As an illustration, utilizing the squareroot function as the aging function and adopting the hour as the unit oftime, after one hour has elapsed, the denominator would be 1 and after 2hours, the denominator would be approximately 1.414, which represents aincrease of nearly 40%. Yet, after three weeks and four weeks, forexample, the denominator in Eq. (1) would be approximately 22.45 and25.92, respectively, yielding a relative increase in the aging functionof about 15% despite the large time change (e.g., 1 week=168 hs). Suchbehavior of the square root function renders it a desirable agingfunction.

Other functions provide similar aging behavior, particularly, yet notexclusively, a real-valued function h(·) having a decreasing slope forincreasing times can be a suitable alternative to the square rootfunction. For example, log(·) is one such function. Yet, since log(·)adopts negative values between 0 and 1, the argument is generallyshifted by the unity, e.g., log(Δt_(v)+1) can be utilized. For anotherexample, the cube root or any higher root of an argument value also canbe suitable as an aging function.

It should be appreciated that, in view of at least in part of theclassification of data described herein, the knowledge generation unit128 generates inferences based on data indicative of consumer behavior.Accordingly, the exchange device 120 effectively can learn specificconsumption preferences of an end-user that consumes content via therendering device 110.

Exchange device 120 can administer consumption of one or more mediaassets based on one or more of the inferences associated withprospective consumption of a media asset. In one aspect, management unit132 can manage a configuration of the prospective consumption of themedia asset based at least on one such inference (e.g., a specific oneof the one or more inferences 137).

In certain scenarios, management of such configuration can be contingentat least on receiving information (e.g., input data) from an end-userthat can consume the media asset. For example, when the media asset is amotion picture, such as video segment, a video streaming session, alinear-programming asset, or the like, a configuration of theprospective consumption of the motion picture can be referred to as aviewing option. To manage the configuration of prospective consumptionof a media asset in such scenarios, the management unit 132 can provide(e.g., generate, transmit, generate and transmit, etc.) a notificationthat the linear-programming asset (e.g., “Star Wars” in Spike TV) isavailable for consumption at a specific time. In one aspect, thenotification can be conveyed to the rendering device 110 as part of datatransmitted via the data and signaling pipe 115. In response, therendering device 110, via the display device 114, for example, canrender indicia (e.g., visual, aural, a combination thereof) conveyingthat the linear-programming asset is available for consumption. Forinstance, the display unit can render a pop-up window displaying amessage identifying such asset. In another additional or alternativeaspect, the management unit 132 can prompt such end-user, as part of thenotification, to consume the linear-programming asset. In one scenario,for example, the foregoing indicia can prompt the user to switch to achannel transmitting the linear-programming asset—e.g., the pop-upwindow can convey the message “Would you like to tune to Star Wars onSpike TV?”

In other scenarios, management of the configuration of prospectiveconsumption of a media asset can comprise administration ofconfiguration(s) of one or more recorded media assets. Such assets canbe recorded in local storage, e.g., retained in memory 136 of theexchange device 120, or in cloud storage, such as a network repository164 that contained in network 160. In one aspect, management unit 132can assign a playback priority to a recorded media asset based at leaston an inference of likelihood of playback of the recorded media asset.Such inference can be generated by the knowledge generation unit 128 andcan be contained in the one or more inferences 137. In oneimplementation, to assign such priority, the management unit 132 canprovide a notification of the playback priority. In such implementationor in an alternative implementation, to assign the playback priority tothe recorded media asset, the management unit 132 can configure theplayback priority in the exchange device 120 or most any other devicethat can retain the recorded media asset and is functionally coupled tothe exchange device 120.

Configuration of the playback priority can include generation of arecord, e.g., a specific instance of metadata 138, in memory 136, therecord being associated with the recorded media asset. It should beappreciated that certain metadata of the metadata 138 can tag (or flag)one or more recorded media assets with, for example, specificinformation associated with instances of consumption of a mediaasset—e.g., metadata can be or can comprise <usage=“viewed multipletimes”> and/or <usage=number of times viewed>. Additional or alternativemetadata of metadata 138 can comprise information associated with theextent of consumption of the media asset, e.g., media asset viewed tocompletion, consumed portion (e.g., a specific percentage) of the mediaasset, and/or fast-forward portion of the media asset. As anotheralternative or additional instance, the metadata of metadata 138 cancomprise information associated with consumption recency, e.g., timeelapsed from initiation recordation of (or otherwise access to) themedia asset and first consumption. As a further alternative or instance,the metadata of metadata 138 can comprise information associated withstate of the media asset at the time of consumption, the stateindicating, for example, the media asset is a recorded asset (e.g., aVOD asset, an nVOD asset, or a locally recorded asset) or the mediaasset is a linear-programming asset.

In another aspect, the management unit 132 can assign a deletionpriority to the recorded media asset based at least on the inference oflikelihood of playback of the recorded media asset. In oneimplementation, to assign such priority, the management unit 132 canprovide a notification of the deletion priority and, in response,implement (e.g., configure) the notification via metadata, for example.Such notification, in one aspect, can be embodied in data transmitted tothe rendering device 110 and rendered, via the display unit 114, forexample. In such implementation or in an alternative implementation, toassign the playback priority to the recorded media asset, the managementunit 132 can configure the deletion priority in the exchange device 120or most any other device that can retain the recorded media asset and isfunctionally coupled to the exchange device 120. As an example, if anend-user has watched a recorded media asset (e.g., one of media asset(s)138) at least 3 times, knowledge generation can generate an inferencebased on such consumption frequency information indicative of anadjustment to a deletion priority of the recorded media asset. In onescenario, the exchange device 120 can transmit a notification to therendering device 110 which, in response, can render indicia (e.g., apop-up window) conveying a configuration menu suggesting that suchdeletion priority be changed from, for example, “delete when no memoryspace is available” to “delete upon end-user request.”

In still another additional or alternative aspect, the management unit132 can assign a scheduling, or queuing, priority for recordation of alinear-programming asset for example. In one scenario, for example, anend-user can have access (e.g., a subscription) to at least an entireseason (e.g., a predetermined group of episodes) of a firstlinear-programming asset (such as “The Office”) and similar access to asecond linear-programming asset (e.g., “Hoarders”). In an initialconfiguration of the exchange device 120, the second linear-programmingasset can have scheduling priority over the second linear-programmingasset. Yet, as the end-user consumes content via the rendering device110 over certain period (e.g., a few weeks), data collected at theexchange device 120 can be indicative that the end-user has notreproduced a single recorded episode of the second linear-programmingasset (e.g., “Hoarders”). Yet, in such period, the data is indicative ofthe end-user having reproduced at least one episode of the firstlinear-programming asset (e.g., “The Office”) one or more times.Accordingly, based at least on such data, the knowledge generation unit128 can generate an inference that permits the management unit 132 toassign or to supply a recommendation to an end-user to assign a higherscheduling priority to the first linear-programming asset.

The exemplary system 180 depicted in FIG. 1B can permit customization ofconsumption of a media asset in a distributed environment (e.g., aclient-server environment). Such environment can be suitable for aexchange device 120 with computational resources that may prevent itfrom processing data and generating one or more inferences as describedherein. For example, in one scenario, the exchange device 120 can be alegacy set-top box with limited computational resources. Yet, byoperating as a client of a network 190, such set-top box can implementat least certain features described herein.

In one implementation, the exchange device 120 can collect data and/orsignaling from the rendering device 110 via the data and signaling pipe115, as described herein, and can transmit at least a portion of suchinformation to a repository 194 contained in a network 190. In oneaspect, at least the portion of the information can be transmitted to adata service that can be implemented by an application layer (notdepicted) at the network 190. In another aspect, a network-based servicecan be associated with the data service and to the repository 194. Thenetwork-based service can comprise, for example, a cloud-based serviceor a web-based service that provides a user interface for an exchangedevice (e.g., a set-top box embodying exchange device 120) havingnetworking functionality. In certain embodiments, such network-basedservice can be implemented by at least one server in an applicationlayer (not depicted) and can enable the functionality of the knowledgegeneration unit 128 and the management unit 132 in accordance withaspects described herein. In certain implementations, the network 190can be substantially the same as the network 160, with the specificfeature of containing the knowledge generation unit 128, the managementunit 132, and the repository 194. In one embodiment, the knowledgegeneration unit 128 and the management unit 132 can be part of anapplication layer (not depicted) in the network 190, whereas therepository 194 can be part of a data layer (not depicted).

The data service can utilize the repository 194. In one aspect, theexchange device 120 can transmit at least a portion of data and/orsignaling securely. To at least such end, in one implementation, theexchange device 120 can have a management client unit 182 that cangenerate a hash of identifying information of the exchange device 120(e.g., personal information of an owner or lessee of such device) andcan utilize the hash to securely transmit at least the portion of thedata and/or information to the repository 194. It should be appreciatedthat generating such hash in order to convey information at therepository 194, which can be associated with the data service, suchidentifying information can be maintained secure while retainingcollected data and/or signaling at the data storage 142 at therepository 194. In certain implementations, the management client unit120 can transmit, to the data storage 142, information comprising dataindicative of consumed media assets, time of consumption, time ofdeliver of a linear-programming asset, and so forth.

The knowledge generation unit 128 and the management unit 132 canoperate in accordance with one or more features described herein. In oneaspect, the knowledge generation unit 128 and the management unit 132can transmit various types of information (e.g., data or metadata, orcombinations thereof) to the repository 194. The exchange device 120,via the management client unit 182, for example, can utilize a hashfunction to access the repository 194 or a functional element thereof inorder to retrieve data indicative of an inference (e.g., a personalizedoption or suggestion). In certain implementations, the exchange device120 can execute the hash-function (periodically, for example) to producehashed account information associated with consumption of media asset atthe rendering device 110, for example. Upon or after generation of thehashed account information, the exchange device 120, via the managementclient unit 182, for example, can utilize the hashed account informationto access (e.g., retrieve) consumption information at the repository194, the consumption information permitting determination or access toone or more inferences in accordance with aspects described herein. Theconsumption information can comprise consumption statistics and relatedmetadata from an account associated with the hashed account information,such statistics and related metadata comprising one or more ofinformation associated with recently viewed linear programming; extentof consumption of at least one (e.g., one, two, more than two, each)recorded media asset that is viewed; number of times a media asset hasbeen consumed; and source of media asset, such as linear programming ornon-linear source (e.g., VOD server or nVOD).

FIG. 2 is a high-level block diagram of an exemplary network 200 inaccordance with one or more aspects of the disclosure. As illustrated,the network 200 comprises a core network platform 210 functionallycoupled to a distribution platform 230 via a data and signaling pipe228. The distribution platform 230 is functionally coupled to atransport network 250 via a data and signaling pipe 248. Each of thedata and signaling pipes 228 and 248 can comprise at least some of thestructural and functional features of other data and signaling pipesdescribed herein. The network is functionally coupled to the exchangedevice 120 via the data and signaling pipe 185. While the exchangedevice 120 is illustrated as comprising the I/O interface(s) 124, itshould be appreciated that such device also can include other functionalelements in accordance with the exemplary embodiments shown at FIGS. 1Aand 1B and aspects described herein. In one embodiment, the core networkplatform 210, the distribution platform 230, the transport network 250and the data and signaling pipes 228 and 248 can embody or can comprisethe network 160. In such embodiment, the network repository 224 canembody or can comprise the network repository 164, and the exchangedevice 120 can comprise the illustrated I/O interface(s) 124 and theknowledge generation unit 128, the management unit 132, the processor(s)150, and the memory 136 having the memory elements shown in FIG. 1A.

In another embodiment, the core network platform 210, the distributionplatform 230, the transport network 250 and the data and signaling pipes228 and 248 can embody or can comprise the network 190. In suchembodiment, at least one server of the server(s) 214 can embody or cancomprise the knowledge generation unit 128 and the management unit 132;and the network repository 224 can embody or can comprise the repository194 and the memory elements shown in FIG. 1B. In addition, in suchembodiment, the bus 226 can embody or can comprise the functionalelements (represented with open-head arrows in FIG. 1B) that permitfunctional coupling between two or more of the knowledge generation unit128, the management unit 132, and the repository 194.

The core network platform 210 can have a packet-switched (PS)architecture. The core network platform 210 can include various networknodes which can be distinguished according to the functionality thereof.As illustrated, the various network nodes can comprise one or moreserver(s) 214, one or more node(s) 218 (e.g., gateway node(s)), and anetwork repository 224. While illustrated as a single entity, thenetwork repository 224 can be distributed in order to provide dataresiliency and other data management advantages. In addition, while corenetwork platform 210 is illustrated as a single block, in one or moreembodiment(s), such platform can be distributed, having a centralizeddeployment site and a plurality of distributed deployment sites.Functionality and architecture of the one or more server(s) 214, the oneor more node(s) 218, and the network repository 224 can be specific, yetnot exclusive, to the particular embodiment of the core network 210. Asan example, in an exemplary embodiment in which the core networkplatform 210 is an internet protocol multimedia subsystem (IMS) network,network repository 224 can be a home subscriber server (HSS); server(s)214 can comprise application server(s), and specific function controlnodes (e.g., Call Session Control Functions (CSCFs), such as servingCSCF (S-CSCF) and interrogating CSCF (I-CSCF)) and proxy servers; andnode(s) 218 can comprise a breakout gateway control function (BGCF), amedia gateway (MGW) and a signaling gateway (SGW), and media gatewaycontrol function (MGCF).

Network nodes, or network elements, in the core network platform 210 canbe functionally coupled through a bus 226, which can permit exchange ofinformation (e.g., data, metadata, signaling, or any combinationthereof) among the server(s) 214, the node(s) 218, and the networkrepository 224. Bus 226 can include a plurality of reference links (Cx,Cr, Dh, Dx, Gm, Ma, Mg, etc.) and associated components, andconventional bus architectures such as address buses, system buses,power buses, and the like.

Distribution platform 230 can comprise one or more signal processingcomponent(s) (not depicted) that can receive and operate on aninformation stream, such as a data stream, a signaling stream, or acombination thereof. In one aspect, such component(s) can perform one ormore operations on the information stream, such encoding, modulation,encryption, multiplexing, up-conversion, down-conversion, combination,and the like. Architecture of the distribution platform 230 can bespecific to the implemented modality exploited for transmission of theinformation stream. Such modality can include wired delivery or wirelessdelivery, and specific protocols for transmission of information such aspacket-switched communication, circuit-switched communication, or thelike. In one embodiment, at least one of such signal processingcomponent(s) can embody a termination system (TS), such as, in one typeof network, a cable modem termination system (CMTS). In anotherembodiment, at least one of the one or more signal processing componentsof distribution platform 230 can embody a network router or a networkswitch (e.g., a digital subscriber line access multiplexer (DSLAM)) fortransmission of information streams based on a PS communicationprotocol, such as internet protocol (IP) (e.g., IPv4 or IPv6). Asillustrated, the distribution platform 230 can comprise a group of oneor more originating nodes 246 that can transmit an information stream ora processed instance thereof.

In certain embodiments, each originating node of the group of one ormore originating nodes 246 can embody or can comprise an edge quadratureamplitude modulation (QAM) node. In other embodiments, each originatingnode of the group of one or more originating nodes 246 can embody or cancomprise a device that consolidates the functionality of a terminationsystem (e.g., a CMTS) and an edge QAM node. In yet other embodiments,each originating node of the group of one or more originating nodes 246can embody or can comprise a network router (e.g., a broadband remoteaccess server (BRAS)) or network switch (e.g., a DSLAM) for transmissionof information streams based on a PS communication protocol (e.g.,internet protocol). In other embodiments, the network 200 can beimplemented, end-to-end or a portion thereof, as an IP orpacket-switched system.

While illustrated as a single block, in one or more embodiment(s), thedistribution platform 230 can be distributed, having a centralizeddeployment site (or plant) and a plurality of hub sites (also referredto as sites). In such embodiment(s), each one of the hub sites cancomprise an edge originating node of the group of one or more edgeoriginating nodes 246.

The distribution platform 230 can receive data (data flows, audiosignals, video signals, any combinations thereof, etc.), metadata,and/or signaling (control instructions, clock signals, etc.) from afunctional element that is, for example, part of core network platform210 or that is functionally coupled thereto. In one scenario, thefunctional element can be a server that supplies a combination of audiosignal and video signal, such as an audiovisual signal comprising avideo asset. The server can be, for example, a content server forpay-per-view programming or video-on-demand assets, an applicationserver, a data server, a telephony server, a backbone network router, orthe like. In such scenario, based on the formatting of the audiovisualsignal, one or more signal processing components (not shown) in thedistribution platform 230 can process (encode, encrypt, modulate,multiplex, up-convert, down-convert, combine, etc.) the audiovisualsignal and supply a resulting audiovisual signal to an edge originatingnode of the group of one or more originating nodes 246. An originatingnode can transmit a plurality of P (a natural number) data streams,conveying at least a portion of the audiovisual signal. It should beappreciated that in certain embodiments, the edge originating node canoperate on the audiovisual signal without reliance on such one or moresignal processing components. In another scenario, a source node (e.g.,a satellite transceiver coupled to an asset source) coupled to thedistribution platform 230 can generate an audiovisual signal, which canbe processed by one or more processing component(s) and supplied to anedge originating node of the one or more originating nodes 246. Suchedge originating node can transmit a plurality of Q (a natural number)data streams conveying at least a portion of the audiovisual signal.

A node of the one or more nodes 218 (e.g., gateway node(s)) can receiveinformation from a server of the one or more servers 214 and relay it,for example, to a session resource manager (SRM) server (not depicted)that can be included is part of the distribution platform 230. Inanother implementation, a server (such as a proxy server) of the one ormore servers 214 can receive information and relay it to the SRM server.

As illustrated, the network 200 comprises a transport network 250 whichcan be a wide area network (WAN) that can be embodied in a wirelessnetwork, a wireline network, or a combination thereof, and supplies dataservice(s) (e.g., television programming, video on demand, Internetservice, packet-switched data or telephony) to a user locationcomprising the exchange device 120. In certain implementations,transport network 250 can be embodied in an optic fiber network, acoaxial cable network, a hybrid fiber coaxial (HFC) network, or awireless network comprising terrestrial wireless links and deep-spacelinks (e.g., satellite links), or any combination thereof. As anillustration, in an embodiment in which the transport network 250 is anHFC network, the data pipe and signaling 248 can comprise several opticfiber links and associated optical functional elements, such asdownstream lasers, light amplifiers, last-mile fiber aggregator node,and the like. In addition, in such embodiment, the transport network 250can comprise various RF amplifiers and coaxial taps to respectivedwellings (e.g., a stationary user location) wherein the exchange device120 can be located and can consume a data service (VOD, nVOD, etc.)provided through the distribution platform 230. In such embodiment, theexchange device 120 can be functionally coupled to a cable modem orother device that serves as the network gateway to the dwelling network(not depicted) from the transport network 250. As another illustration,in an embodiment in which the transport network 250 is a wired broadbandPS network, the data pipe and signaling 248 can comprise Ethernet links,and can include network routers such as BRASs and network switches, suchas DSLAMs. The network switches can be functionally coupled to homegateways (e.g., DSL modems) in dwellings in which the exchange device120 can consume data services provided through the distribution platform230.

FIG. 3 is a block diagram of an exemplary embodiment 300 of the exchangedevice 120 for generation of recommendations and/or for administrationof consumption of media assets in accordance with one or more aspects ofthe disclosure. As described herein, certain features of suchadministration can be automated. As described herein, the exchangedevice 120 comprises a memory 320 that can have computer-executableinstructions that can embody or can comprise knowledge generation unit132 and management unit 128. In addition, in the illustrated embodiment,the exchange device 120 can comprise one or more I/O interfaces 148 thatcan embody one or more application processing interfaces (APIs).

In one aspect, the exchange device 120 can comprise the processor(s) 310which can be functionally coupled to the memory 320 and can beconfigured, by the computer-executable instructions, to receive dataindicative of consumption of a plurality of media assets. In one aspect,the processor(s) 310 can embody or can comprise the processor(s) 150. Incertain implementations, the consumption can be current consumption ofat least a first one of the plurality of media assets. In otherimplementations, the consumption can be historical consumption of atleast a second one of the plurality of media assets. Based at least on aportion of such data, in one aspect, the processor can be configured bythe computer-executable instructions to provide an inference associatedwith prospective consumption of a specific media asset of the pluralityof media assets. In another aspect, as described herein, the processorcan be configured by the computer-executable instructions to manage aconfiguration of the prospective consumption of the specific media asset(e.g., a recorded asset) based at least on the inference. Suchconfiguration can embody or can comprise an instance of administrationof consumption of the specific media asset.

In one scenario, to manage the configuration, the processor(s) 310 canbe configured, by the computer-executable instructions, to assign aplayback priority to a recorded media asset (e.g., one of the one ormore media assets 140) based at least on an inference of likelihood ofplayback of the recorded media asset. The playback priority of therecorded media asset can be embodied in metadata (e.g., retained in oneof the metadata 138) representative of placement of such asset in anordered list of media assets to be reproduced and/or rendered in therendering device 110. In another scenario, to manage the configuration,the processor(s) 310 can be further configured, by thecomputer-executable instructions, to assign a deletion priority to arecorded media asset based at least on an inference of likelihood ofplayback of the recorded media asset. Similarly to the playbackpriority, the deletion priority of the recorded media asset can beembodied in metadata (e.g., retained in one of the metadata 138)representative of placement of such asset in an ordered list of mediaassets to be removed from the memory 320.

As described herein, to provide the inference, the processor(s) 310 canbe further configured to generate the inference in accordance with oneor more aspects described herein. For instance, in one implementation,the processor(s) 310 can execute the computer-executable instructionsthat embody the knowledge generation unit 132. In one aspect, to providethe inference, the processor can be configured, by thecomputer-executable instructions, to classify the data into at least twocategories of data comprising: a first category of data suitable forinferring the prospective consumption of the specific media asset; and asecond category of data unsuitable for inferring the prospectiveconsumption of the specific media asset.

In certain implementations, to provide the inference, the processor canbe further configured to receive the inference. In such implementations,for example, the processor(s) 210 can receive the inference from acomponent external to the exchange device 120.

FIG. 4 is a block diagram of an exemplary embodiment 400 of the exchangedevice 120 in accordance with one or more aspects of the disclosure. Inthe illustrated embodiment, the exchange device 120 comprises a group ofone or more I/O interfaces 404, a group of one or more processors 408, amemory 416, and a bus 412 that functionally couples (e.g.,communicatively couples) two or more of the functional elements of theexchange device 120 including the group of one or more processors 408 tothe memory 416. In certain scenarios, the group of one or moreprocessors 408 can comprise a plurality of processors that can exploitconcurrent computing.

Functionality of the exchange device 120 can be configured by a group ofcomputer-executable instructions (e.g., programming code instructions orprogramming modules) that can be executed by at least one processor ofthe one or more processors 408. Generally, programming modules cancomprise computer code, routines, objects, components, data structures(e.g., metadata objects, data object, control objects), and so forth,that can be configured (e.g., coded or programmed) to perform aparticular action or implement particular abstract data types inresponse to execution by the at least one processor. For example, afirst group of computer-executable instructions can configure logicthat, in response to execution by the at least one processor, can enablethe exchange device 120 to operate as a computing device (e.g., aserver), a gateway node, or the like.

Data and computer-accessible instructions, e.g., computer-readableinstructions and computer-executable instructions, associated withspecific functionality of the network node 502 can be retained in memory416. Such data and instructions can permit implementation, at least inpart, of the latency-based routing, and related load balancing, ofqueries in accordance with one or more aspects of the disclosure. In oneaspect, the computer-accessible instructions can embody any number ofprogramming code instructions or program modules that permit specificfunctionality. In the subject specification and annexed drawings, memoryelements are illustrated as discrete blocks, however, such memoryelements and related computer-accessible instructions (e.g.,computer-readable and computer-executable instructions), and data canreside at various times in different storage elements (registers, memorypages, files, databases, memory addresses, etc.; not shown) in memory416.

Data storage 420 can comprise a variety of data, metadata, or both,associated with latency-based routing, and relating load balancing, inaccordance with aspects described herein.

Memory 416 also can comprise one or more computer-executableinstruction(s) for implementation of specific functionality of theexchange device 120 in connection with the dynamic provisioning ofcommunication resources described herein. Such computer-executableinstructions can be retained as a memory element labeled knowledgegeneration instruction(s) 418. In one aspect, as described herein,knowledge generation instruction(s) 418 can be stored as animplementation (e.g., a compiled instance) of one or morecomputer-executable instructions that implement and thus provide atleast the functionality of the methods described herein. Knowledgegeneration instruction(s) 418 also can be transmitted across some formof computer readable media. It should be appreciate that differentfunctionality instruction(s) can render physically alike network nodesinto functionally different components (e.g., a server and a datamanager unit), with functional differences dictated by logic (e.g.,computer-executable instructions and data) specific to each one of suchnetwork nodes and defined by the knowledge generation instruction(s)418. In an exemplary configuration in which the exchange device 120embodies a server, the knowledge generation instruction(s) 418 cancomprise or embody computer-accessible instructions that, in response toexecution by a processor (e.g., a processor of the one or moreprocessors 408), can permit the server to evaluate performancecondition(s) of the server and retain a record of such condition(s) inmemory.

Memory 416 can be embodied in a variety of computer-readable media.Exemplary computer-readable media can be any available media that isaccessible by a processor in a computing device, such as one processorof the group of one or more processors 408, and comprises, for example,both volatile and non-volatile media, removable and non-removable media.As an example, computer-readable media can comprise “computer storagemedia,” or “computer-readable storage media,” and “communicationsmedia.” Such storage media can be non-transitory storage media.“Computer storage media” comprise volatile and non-volatile, removableand non-removable media implemented in any methods or technology forstorage of information such as computer readable instructions, datastructures, program modules, or other data. Exemplary computer storagemedia comprises, but is not limited to, RAM, ROM, EEPROM, flash memoryor other memory technology, CD-ROM, digital versatile disks (DVD) orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe utilized to store the desired information and which can be accessedby a computer or a processor therein or functionally coupled thereto.

Memory 416 can comprise computer-readable non-transitory storage mediain the form of volatile memory, such as random access memory (RAM),electrically erasable programmable read-only memory (EEPROM), and thelike, or non-volatile memory such as read only memory (ROM). In oneaspect, memory 416 can be partitioned into a system memory (not shown)that can contain data and/or programming modules that enable essentialoperation and control of the exchange device 120. Such program modulescan be implemented (e.g., compiled and stored) in memory element 422,referred to as operating system (OS) instruction(s) 422, whereas suchdata can be system data that is retained in memory element 424, referredto as system data storage 424. The OS instruction(s) 422 and system datastorage 424 can be immediately accessible to and/or are presentlyoperated on by at least one processor of the group of one or moreprocessors 408. The OS instruction(s) 422 can embody an operating systemfor the network node. Specific implementation of such OS can depend inpart on architectural complexity of the exchange device 120. Highercomplexity affords higher-level OSs. Example operating systems caninclude Unix, Linux, iOS, Windows operating system, and substantiallyany operating system for a computing device. In certain scenarios, theoperating system embodied in OS instruction(s) 422 can have differentlevels of complexity based on particular configuration of the exchangedevice 120.

Memory 416 can comprise other removable/non-removable,volatile/non-volatile computer-readable non-transitory storage media. Asan example, memory 416 can include a mass storage unit (not shown) whichcan provide non-volatile storage of computer code, computer readableinstructions, data structures, program modules, and other data for theexchange device 120. A specific implementation of such mass storage unit(not shown) can depend on desired form factor of the exchange device 120and space available for deployment thereof. For suitable form factorsand sizes of the exchange device 120, the mass storage unit (not shown)can be a hard disk, a removable magnetic disk, a removable optical disk,magnetic cassettes or other magnetic storage devices, flash memorycards, CD-ROM, digital versatile disks (DVD) or other optical storage,random access memories (RAM), read only memories (ROM), electricallyerasable programmable read-only memory (EEPROM), or the like.

Features of generation personalized options for consumption of mediaassets can be performed, at least in part, in response to execution ofsoftware components by a processor. The software components can includeone or more implementations (e.g., encoding) of knowledge generationinstruction(s) 418. In particular, yet not exclusively, to provide thespecific functionality of the exchange device 120, a processor of theone or more processors 408 in the exchange device 120 can execute atleast a portion of the computer-accessible instructions in knowledgegeneration instruction(s) 418.

In general, a processor of the group of one or more processors 408 canrefer to any computing processing unit or processing device comprising asingle-core processor, a single-core processor with software multithreadexecution capability, multi-core processors, multi-core processors withsoftware multithread execution capability, multi-core processors withhardware multithread technology, parallel platforms, and parallelplatforms with distributed shared memory (e.g., a cache). In addition orin the alternative, a processor of the group of one or more processors408 can refer to an integrated circuit with dedicated functionality,such as an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), acomplex programmable logic device (CPLD), a discrete gate or transistorlogic, discrete hardware components, or any combination thereof designedto perform the functions described herein. In one aspect, processorsreferred to herein can exploit nano-scale architectures such as,molecular and quantum-dot based transistors, switches and gates, inorder to optimize space usage (e.g., improve form factor) or enhanceperformance of the computing devices that can implement the variousaspects of the disclosure. In another aspect, the one or more processors408 can be implemented as a combination of computing processing units.

The one or more input/output (I/O) interfaces 404 can functionallycouple (e.g., communicatively couple) the exchange device 120 to anotherfunctional element (component, unit, server, gateway node, repository,etc.) or network 160, for example. Functionality of the exchange device120 that is associated with data I/O or signaling I/O can beaccomplished in response to execution, by a processor of the group ofone or more processors 408, of at least one I/O interface retained inmemory element 428. Such memory element is represented by the block I/Ointerface(s) 428. In some embodiments, the at least one I/O interfaceembodies an API that permit exchange of data or signaling, or both, viaan I/O interface of I/O interface(s) 404. In certain embodiments, theone or more I/O interfaces 404 can include at least one port that canpermit connection of the exchange device 120 to other functionalelements of the exemplary network environment 100. In one or morescenarios, the at least one port can comprise network adaptor(s) such asthose present in reference links, and other network nodes. In otherscenarios, the at least one port can include one or more of a parallelport (e.g., GPIB, IEEE-1284), a serial port (e.g., RS-232, universalserial bus (USB), FireWire or IEEE-1394), an Ethernet port, a V.35 port,or the like. The at least one I/O interface of the one or more I/Ointerfaces 404 can enable delivery of output (e.g., output data, outputsignaling) to such functional elements. Such output can represent anoutcome or a specific action of one or more actions described herein,such as the actions in the method of FIG. 4. Specific configurations, ordeployments, of the one or more I/O interfaces 404 can include at leastone HDMI.

In certain embodiments, the exchange device 120 can comprise afunctionality specific platform (not shown) which can include one ormore components the permit functionality of the exchange device 120. Inone embodiment, a component of the one or more components can be afirmware component which can have dedicated resources (e.g., aprocessor, software, etc.) to implement certain functions that supportimplementation of or implement at least part of the functionality of theexchange device 120. In another embodiment, the functionality specificplatform (not shown) can include at least a portion of the one or moreprocessors 408 which can be dedicated to execution of a part or all ofthe knowledge instruction(s) 418, thus relieving at least some of thecomputational load from the one or more processors 408 for otheroperation of the exchange device 120.

Bus 412 represents one or more of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. As an example, such architectures cancomprise an Industry Standard Architecture (ISA) bus, a Micro ChannelArchitecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video ElectronicsStandards Association (VESA) local bus, an Accelerated Graphics Port(AGP) bus, and a Peripheral Component Interconnects (PCI), a PCI-Expressbus, a Personal Computer Memory Card Industry Association (PCMCIA),Universal Serial Bus (USB), and the like.

In view of the various aspects of generating personalized options forconsumption of media assets comprising linear-programming assets orrecorded media assets, such as those described herein, exemplary methodsthat can be implemented in accordance with the disclosure can be betterappreciated with reference to the exemplary flowcharts in FIGS. 5-7. Forsimplicity of explanation, the exemplary methods disclosed herein arepresented and described as a series of actions (also referred to assteps), pictorially represented with a block. However, it is to beunderstood and appreciated that implementation, and related advantages,of such methods is not limited by the order of actions, as some actionsmay occur in different orders and/or concurrently with other actionsfrom that shown and described herein. For example, the various methods(also referred to as processes) of the disclosure can be alternativelyrepresented as a series of interrelated states or events, such as in astate diagram. Moreover, when disparate functional elements (networknodes, units, etc.) implement different portions of the methods of thedisclosure, an interaction diagram or a call flow can represent suchmethods or processes. Furthermore, not all illustrated actions may berequired to implement a method in accordance with the subjectdisclosure.

The method(s) disclosed throughout the subject specification and annexeddrawings can be stored on an article of manufacture, orcomputer-readable storage medium, to facilitate transporting andtransferring such methods to computing devices (e.g., desktop computers,mobile computers, mobile telephones, and the like) for execution, andthus implementation, by a processor or for storage in a memory.

FIG. 5 is a flowchart of an exemplary method 500 for handling (e.g.,processing, transmitting, and/or consuming) content in accordance withone or more aspects of the disclosure. The exemplary method 500 can beimplemented (e.g., performed or executed) by one or more computingdevices (e.g., exchange device 120), or a processor therein orfunctionally coupled thereto. At block 510, data indicative of currentconsumption of content, such as a plurality of content assets, isreceived. Such block can be referred to as a receiving action. Asdescribed herein, the plurality of content assets can comprise one ormore linear-programming content assets or one or more time-shifted,e.g., recorded, content assets (e.g., one or more video-on-demand (VOD)assets, one or more network-stored VOD (nVOD) assets, or the like). Inone aspect, the receiving action can comprise receiving data indicativeof rendering (display, rewind, pause, etc.) of a linear-programmingmedia asset. In another aspect, the receiving action can comprisereceiving data indicative of playback of a recorded content asset.

At block 520, an inference associated with prospective consumption of acontent asset of the plurality of content assets is generated based atleast on a portion of the data received at block 510. In one embodiment,the knowledge generation unit 128 can generate the inference. Block 520can be referred to as a generating action and, in one aspect, cancomprise classifying the data into at least two categories of data. Asdescribed herein, in certain embodiments, the at least two categories ofdata can comprise a first category of data suitable for inferring theprospective consumption of the content asset and a second category ofdata unsuitable for inferring the prospective consumption of thespecific content asset. As described herein, the first category of datais indicative of end-user consumption behavior over a period of time(e.g., a consumption trend) and can comprise the portion of the datautilized for generation of the inference.

As described herein, classifying the data received at block 510 in suchcategories can permit discriminating data into data that containsbehavioral information of a consumer of a content asset and data thatrepresents operation of a device rendering one or more of the contentassets of the plurality of content assets. In one aspect, classifyingthe received data into the second category of data can comprisedetermining that an interface (e.g., one of I/O interface(s) 112)contained in or functionally coupled to a device for rendering thespecific content asset (e.g., rendering device 110) is switched off fora specific period, and assigning at least a portion of the data receivedduring the specific period to the second category of data.

At block 530, the prospective consumption of the content asset ismanaged based at least on the inference generated at block 520. Block530 can be referred to as a managing action. In one aspect, the managingaction can comprise providing a notification that a specificlinear-programming asset is available for consumption. In anotheraspect, the managing action also can comprise prompting an end-user, aspart of the notification, to consume the linear-programming asset. Themanaging action can administer consumption features of time-shifted,e.g., recorded, content assets. In one administration scenario, themanaging action can comprise assigning a playback priority to a recordedcontent asset based at least on the inference generated at block 520. Insuch scenario, the inference relied on, at least in part, can be aninference of likelihood of playback of the recorded content asset. Inone aspect, assigning the playback priority can comprise configuring theplayback priority in a device that retains the recorded content asset,such as exchange device 120. For instance, configuring the playbackpriority can include configuring metadata associated with a datastructure containing the recorded content asset. In another additionalor alternative aspect, assigning the playback priority can compriseproviding (e.g., generating and communicating) a notification of theplayback priority. In yet another additional or alternative aspect, themanaging action can comprise a recording, or scheduling, priority. In afurther aspect or alternative aspect, the managing action can compriseassigning a deletion priority to the recorded content asset based atleast on the inference generated at block 520. Such inference can be,for example, the inference of likelihood of playback of the recordedcontent asset. In another implementation, similarly to administration ofplayback priorities, assigning the deletion priority to the recordedcontent asset can include providing a notification of the deletionpriority, wherein assigning such deletion priority can includeconfiguring the deletion priority in a device that retains the recordedcontent asset.

As described herein, block 520 can comprise classifying the data into atleast a first category of data suitable for inferring the prospectiveconsumption of the content asset and a second category of datanon-suitable for inferring the prospective consumption of the specificcontent asset. In certain scenarios, exemplary method 600 in FIG. 6 canembody block 520. Accordingly, it should be appreciated that theexemplary method 600 is an exemplary method for classifying dataassociated with consumption of content assets into a category of datasuitable for generating an inference of prospective consumption ofcontent assets in accordance with one or more aspects of the disclosure.In certain embodiments, the computing device that can implement theexemplary method 400 also can implement the exemplary method 600. Atblock 610, data indicative of consumption of a content asset isreceived. In one implementation, such block can be at least a portion ofblock 410. At block 620, it is determined if a rendering device (e.g.,rendering device 110) is turned on. In one embodiment, suchdetermination can be made by monitoring signaling from an HDMI (e.g.,one of I/O interface(s)) included in the rendering device. In a scenarioin which the rendering device is not turned on, at block 630, the dataindicative of consumption of the content asset is classified asnon-suitable for generating an inference of prospective consumption ofthe content asset. In a scenario in which the rendering device is turnedon, flow is directed to block 640, at which it is determined if thecontent asset is consumed to at least a predetermined extent (e.g., 90%of the content asset has been consumed). In one embodiment, a level ofconsumption of the content asset can be extracted from at leastsignaling (e.g., control input 104) received from the HDMI included inthe rendering device, such signaling received at another I/O interfacein the rendering device.

In a scenario in which the content asset is not consumed to at least thepredetermined extent, flow is directed to block 630. Yet, in theconverse scenario, flow is directed to block 650 at which it isdetermined if a participation level fulfills a presence criterion. Inone aspect, the presence criterion can establish one or more specifictypes and/or levels of information (data, metadata, and/or signaling)indicative of the content asset being consumed (e.g., an end-user iswatching a recorded movie) that can be available in order to establish,at least in part, that the content asset is actively consumed. Forexample, one of such types of information can comprise changes in volumeof audio associated with the content asset. For another example, anotherone of such types of information can comprise switching a channel thatis being tuned. For yet another example, yet another one of such typesof information can comprise one or more of fast-forwarding, rewinding,or pausing the content asset. As described herein, the informationindicative of the content asset being consumed can be extracted, atleast in part, from control information (e.g., control input 104)received at the rendering device. For a participation level fulfillingthe presence criterion, the flow is directed to block 660, at which thedata indicative of consumption of the content asset is classified asdata suitable for generating an inference of prospective consumption ofthe content asset.

FIG. 7 illustrates a flowchart of an exemplary method 700 for providinga viewing suggestion queue according to one or more aspects of thedisclosure. In certain scenarios, the exemplary method 700 can embodyblock 520. While illustrated with a viewing suggestion queue (alsoreferred to as a suggestion queue), the exemplary method 700 can becarried out for generation of any inference associated with consumptionof a content asset. In certain embodiments, the computing device or theprocessor functionally coupled thereto can implement the exemplarymethod 400, and also may implement the subject exemplary method 700. Atblock 710, each content asset of a set of one or more content assets isinitialized, or initially treated, as unchecked. At block 715, anunchecked content asset is selected. In one embodiment, the managementunit 132 can perform blocks 710 and 715, referred to as an initializingaction. In another embodiment, the knowledge generation unit 128 canperform such blocks.

At block 720 it is determined if consumption (e.g., rendering) of theunchecked content asset is above a first threshold (e.g., 85% of totalduration of asset). In one aspect, the first threshold can beconfigurable or statically determined (e.g., hardcoded into theoperation of knowledge generation unit 128). In response to consumptionbeing at or below the first threshold, the unchecked content asset isclassified as checked at block 725. In response to consumption beingabove the first threshold, it is determined at block 730 if rendering ofthe unchecked content asset is advanced (e.g., fast-forwarded), duringconsumption, for a net time interval (e.g., cumulative period of one ormore fast-forward events) that is less than a specific portion (e.g.,25%) of duration of such asset. In the negative case, flow is directedto block 725. Yet, in response to the unchecked content asset beingfast-forwarded for a net time interval greater than or equal to thespecific portion of the duration of the unchecked content asset, flow isdirected to block 735 at which it is determined if such asset is part ofa series (e.g., a premium television season of several episodes). Anaffirmative determination results in flow being directed to block 740,at which information indicative of a forthcoming content asset in theseries is added to a suggestion queue. In one aspect, the suggestionqueue can be contained in the one or more inferences 137. In thealternative, in response to the unchecked content asset not being partof a series, it is determined if such asset is consumed several times.In the affirmative case, information indicative of the unchecked contentasset is incorporated into the suggestion queue for repeat viewing. Inone embodiment, the knowledge generation unit 128 can perform one ormore of blocks 720 through 750.

Upon or after implementation of block 725, flow is directed to block 755at which it is determined if one or more unchecked content assets remainunselected. An affirmative determination leads to block 715, whereas anegative determination leads to block 760 at which a suggestion in thesuggestion queue is supplied, for example, to a device, which can be anend-user device or any device functionally coupled (e.g.,communicatively coupled) to the computing device that performs thesubject exemplary method 700. Block 760 can be referred to as asupplying action and, in one aspect, can comprise transmittinginformation (e.g., data and/or metadata) indicative of the suggestion.It should appreciated that the suggestion is one example of an inferencethat can be generated by the exchange device 120, via the knowledgegeneration unit, for example, according to one or more aspects describedherein. In one embodiment, the management unit 132 can perform blocks755 and knowledge generation unit 128 can perform block 760.

In view of the subject specification and annexed drawings, when comparedwith conventional technologies for generation of options for consumptionof content (e.g., media assets), various advantages of the disclosureover such technologies emerge. For example, the disclosure can provideoptions for automated administration of consumption of recorded assetsbeing stored locally and/or remotely in a network repository.

While the systems, apparatuses, and methods have been described inconnection with exemplary embodiments and specific examples, it is notintended that the scope be limited to the particular embodiments setforth, as the embodiments herein are intended in all respects to beillustrative rather than restrictive.

Unless otherwise expressly stated, it is in no way intended that anyprotocol, procedure, process, or method set forth herein be construed asrequiring that its acts or steps be performed in a specific order.Accordingly, in the subject specification, where a description of aprotocol, procedure, process, or method does not actually recite anorder to be followed by its acts or steps or it is not otherwisespecifically stated in the claims or descriptions that the steps are tobe limited to a specific order, it is no way intended that an order beinferred, in any respect. This holds for any possible non-express basisfor interpretation, including: matters of logic with respect toarrangement of steps or operational flow; plain meaning derived fromgrammatical organization or punctuation; the number or type ofembodiments described in the specification or annexed drawings, or thelike.

It will be apparent that various modifications and variations can bemade without departing from the scope or spirit of the subjectdisclosure. Other embodiments will be apparent from consideration of thespecification and practice disclosed herein. It is intended that thespecification and examples be considered as non-limiting illustrationsonly, with a true scope and spirit of the subject disclosure beingindicated by the following claims.

What is claimed is:
 1. A computer-implemented method, comprising:receiving, at computing equipment, data related to one or more mediaassets, wherein the data comprises information about user interactionwith the one or more media assets; generating, at the computingequipment, based on the received information, a predictive inferenceregarding presentation of a particular media asset; and performing,based on the predictive inference, an action related to presenting theparticular media asset on one or more user devices.
 2. The method ofclaim 1, further comprising: categorizing the data into categories ofdata comprising: a first category of data suitable for inferring alikelihood of presentation of the particular media asset, and a secondcategory of data unsuitable for inferring the likelihood of presentationof the particular media asset, wherein a portion of the data iscategorized in the first category.
 3. The method of claim 1, whereinreceiving, at the computing equipment, data related to the one or moremedia assets comprises receiving data indicative of rendering of alinear-programming media asset.
 4. The method of claim 1, whereinreceiving, at the computing equipment, data related to the one or moremedia assets comprises receiving data indicative of rendering of avideo-on-demand media asset.
 5. The method of claim 1, wherein thepredictive inference is generated in response to detecting occurrence ofan event or is generated periodically at predetermined times.
 6. Themethod of claim 1, wherein the action related to presenting theparticular media asset on the one or more user devices comprisesproviding a notification that the particular media asset is availablefor presentation.
 7. The method of claim 6, wherein the notificationcomprises a selectable prompt to commence the presentation of theparticular media asset.
 8. The method of claim 1, wherein receiving, bythe computing device, the data related to the one or more media assetscomprises receiving data indicative of playback of a recorded mediaasset, and wherein the predictive inference indicates a likelihood ofplayback of the recorded media asset.
 9. The method of claim 8, whereinthe action comprises assigning, based on the predictive inference, aplayback priority to the recorded media asset.
 10. The method of claim8, wherein the action comprises assigning, based on the predictiveinference, a deletion priority to the recorded media asset.
 11. Acomputer-implemented system, comprising: input/output (I/O) circuitryconfigured to: receive, at computing equipment, data related to one ormore media assets, wherein the data comprises information about userinteraction with the one or more media assets; control circuitryconfigure to: generate, at the computing equipment, based on thereceived information, a predictive inference regarding presentation of aparticular media asset; and perform, based on the predictive inference,an action related to presenting the particular media asset on one ormore user devices.
 12. The system of claim 11, wherein the controlcircuitry is configured to: categorize the data into categories of datacomprising: a first category of data suitable for inferring a likelihoodof presentation of the particular media asset, and a second category ofdata unsuitable for inferring the likelihood of presentation of theparticular media asset, wherein a portion of the data is categorized inthe first category.
 13. The system of claim 11, wherein the receiveddata related to the one or more media assets comprises data indicativeof rendering of a linear-programming media asset.
 14. The system ofclaim 11, wherein the received data related to the one or more mediaassets comprises receiving data indicative of rendering of avideo-on-demand media asset.
 15. The system of claim 11, wherein thecontrol circuitry is configured to generate the predictive inference inresponse to detecting occurrence of an event or periodically atpredetermined times.
 16. The system of claim 11, wherein the controlcircuitry is configured to, in performing the action related topresenting the particular media asset on the one or more user devices,provide a notification that the particular media asset is available forpresentation.
 17. The system of claim 16, wherein the notificationcomprises a selectable prompt to commence presentation of the particularmedia asset.
 18. The system of claim 11, wherein: the control circuitryis configured to, in receiving the data related to the one or more mediaassets, receive data indicative of playback of a recorded media asset;and the predictive inference indicates a likelihood of playback of therecorded media asset.
 19. The system of claim 18, wherein the controlcircuitry is configured to perform the action by assigning, based on thepredictive inference, a playback priority to the recorded media asset.20. The system of claim 18, wherein the control circuitry is configuredto perform the action by assigning, based on the predictive inference, adeletion priority to the recorded media asset.